CN101715232A - Positioning method of weighted wireless sensor network nodes based on RSSI and LQI - Google Patents

Abstract

The invention relates to a positioning method of weighted wireless sensor network nodes based on an RSSI and an LQI, which is characterized in that (1) the parameters of the RSSI and the LQI, which can be acquired easily from a hardware register, are used for positioning, thus the method can be realized easily and has few required hardware resources; (2) an LQI ranging model obtained by fitting experimental data is combined with an RSSI ranging model to select anchor nodes; and (3) an RSSI value and an LQI value which pass through an average filter are weighted and combined, an improved weighted centroid algorithm is used for estimating the positions of nodes to be detected, the data is broadcasted to cluster nodes, and then, the data is uploaded to a monitoring centre through a wired network. The positioning method of invention has the advantages of high positioning accuracy without being influenced by the environment easily, easy implementation of hardware, lower cost and smaller computation complexity.

Description

Wireless sensor network node locating method based on RSSI and LQI weighting

Technical field:

The present invention relates to wireless sensor network, the wireless sensor network node locating method that be specifically related to a kind of low computation complexity, is easy to realize based on acknowledge(ment) signal intensity indication RSSI (Received Signal Strength Indicator) and link-quality indication LQI (link quality indicator) weighting.

Background technology:

Wireless sensor network (Wireless Sensor Networks, WSN) location technology in is very important, if the data of sensor measurement do not have corresponding position information, so these data almost without any practical value.

According to whether relying on measuring distance in the position fixing process, can be divided into location technology based on (range-based) and (range-free) that need not find range that find range.Based on distance or the angle information of the location technology of finding range, use trilateration, triangulation or maximal possibility estimation positioning mode to provide precision higher node location information by point-to-point between measured node.The location algorithm of non-distance measuring according to the information such as connectedness of network use centroid algorithm, DV-Hop algorithm or subtriangular in the some method of testing (ApproximatePoint-In-Triangulation Test APIT) provides the node location information of coarseness.The coarse grained location information that location algorithm provided of non-distance measuring is enough for the application in most of wireless sensor networks; And need be based on needed additional hardware equipment in the location algorithm of range finding.So the location technology of non-distance measuring is widely adopted in wireless sensor network.At present, the node of a small amount of known location obtains the positional information of other unknown node in the general using wireless sensor network, and the node of these known location is commonly referred to anchor node, and unknown node is called node to be measured or unknown node.

Existing non-distance measuring localization method is extensive use of the RSSI parameter.RSSI is the indication of received signal intensity, is present in the packet between any one information source and the stay of two nights.Its range measurement principle is under the condition of known transmit power, measures received power at receiving node, calculates propagation loss, uses the signal propagation model of theory or experience that propagation loss is converted into distance, and this technology is mainly used the RF signal.Its main source of error be the modeling complexity of the signal propagation model that causes of environmental impact such as reflection, multipath transmisstion, non line of sight (Non-Line-Of-Sight, NLOS), problem such as antenna gain all can produce significantly different propagation loss to same distance.LQI is the link-quality indication, characterizes the energy and the quality of receiving data frames.Its size calculates and offer last layer based on signal strength signal intensity and detected signal to noise ratio (snr) by MAC (media access control) layer, and is general relevant with the probability that correctly receives Frame.RSSI value and LQI value can obtain when Frame of the every reception of ZigBee transceiver module, the variation of the variation of timely reflected signal intensity and the interference that is subjected to.The dynamic range of LQI is bigger than RSSI, and higher resolution is arranged.The LQI value is incorporated the distance estimations algorithm will make raising based on the ranging technology of RSSI space.

Therefore, only find range certainty of measurement and reliability are descended greatly based on the RSSI value.For example publication number is that (number of patent application: CN200810099378.6) patent name is in " a kind of wireless sensor network node positioning method based on RSSI " for the CN101378592 title, it with the distance between the anchor node and signal strength information as a reference, RSSI value between mobile node and the anchor node is carried out verification, revise the weight of anchor node, obtain the node locating coordinate the unknown node position.But owing to only adopt the RSSI parameter to position, its positioning accuracy must be subjected to following factor affecting:

Actual application environment than the ecotopia complexity many, exist uncertainties such as multipath interference, diffraction, barrier, influence the RSSI reading;

2. the situation that the RSSI value of anchor node that receives and unknown node can occur equating can think that at this moment unknown node appears near the position of anchor node, and it is far away in fact to be separated by;

3.RSSI value is subjected to the influence of transmitter power, makes battery-powered system in a large number for wireless sensor network is this, battery voltage in use for some time reduces also can influence the RSSI value;

4.RSSI precision for comparatively accurate range finding, be nowhere near, error is bigger.

In addition, because RSSI value is after distance surpasses certain threshold value, variation tendency is very not obvious, therefore can not be by concrete radio frequency chip detection, so its orientation distance is very limited.Based on above reason, must design and adopt new method, can either inherit based on the non-distance measuring method hardware of RSSI realize simple, obtain conveniently, characteristics that computation complexity is little, also to introduce new parameter and overcome above-mentioned shortcoming.

Summary of the invention:

Technical problem to be solved by this invention is at above-mentioned existing in prior technology problem, a kind of positioning accuracy height is provided, is difficult for affected by environmently, hardware is easy to realize, cost is lower, the wireless sensor network node locating method based on RSSI and LQI that computation complexity is less.

The present invention solves the problems of the technologies described above the technical scheme that is adopted:

[I] introduces LQI as the parameter of considering that improves positioning accuracy and scope, and simulates the range finding model of LQI by experiment.The LQI range-viewfinder formula that obtains of data fitting is as follows by experiment in the present invention:

L(d)＝L(d ₀)-10nlg(d/d ₀)+X _δ；

[II] carries out choosing of anchor node with RSSI and LQI Combined Treatment.

[III] will be weighted combination by the RSSI value and the LQI value of average filter, utilize improved weighted mass center algorithm to carry out the unknown node location estimation.

Method of the present invention comprises the steps:

(1), after unknown node enters network, transmitting power is transferred to minimum value and is sent Location Request LOC_REQ, after receiving the answer LOC_Reply of anchor node, if meeting the requirements, anchor node RSSI value and LQI value then this anchor node is added to anchor node in this position fixing process, otherwise strengthen the unknown node transmitting power and send Location Request LOC_REQ once more, meet the required anchor node number in location up to finding.

(2), when the beacon frame that receives anchor node when unknown node outnumbers a certain threshold value, just think that the degree of communication of unknown node and anchor node is good.Unknown node is determined good around own anchor node m, and notes ID number of anchor node this moment, simultaneously the anchor node information of establishing is sent to telegon Coordinator node.

(3), after telegon Coordinator node receives the information of unknown node, send beacon frame and communicate by letter with the anchor node in the information.After anchor node was received beacon frame, periodically broadcast beacon frame was given telegon Coordinator node.

(4), after telegon Coordinator node receives beacon frame, the RSSI and the LQI of same anchor node got assembly average, telegon Coordinator is big or small according to the RSSI value of receiving anchor node and LQI value, and anchor node is sorted, and sets up three set:

[I] anchor node set: Anchor_set={a ₁, a ₂..., a _m;

The RSSI value set of [II] anchor node correspondence: RSSI_set={r ₁, r ₂... r _m; r ₁＞r ₂＞...＞r _m

The LQI value set of [III] anchor node correspondence: LQI_set={l ₁, l ₂..., l _m; l ₁＞l ₂＞...＞l _m

(5), LQI fitting formula L (d)=L (d that obtains according to experimental data ₀)-10n lg (d/d ₀)+X _δWith RSSI range finding model anchor node is carried out preferably, in the formula, d is the distance between the transmitter and receiver, d ₀Be reference distance, X _δBe that average is zero, variance is the random noise variable of δ, in RSSI_set and LQI_set set, select the higher anchor node of LQI value earlier, under this constraints, it is individual to select the higher anchor node n of RSSI value from the higher anchor node of LQI value again, draws the anchor node coordinate set and is:

Position_set＝{(x ₁，y ₁)，(x ₂，y ₂)，…，(x _n，y _n)}

(6), telegon Coordinator node draws the unknown node coordinate according to improved weighted mass center algorithm, broadcast data is uploaded to Surveillance center through cable network then to aggregation node.

Characteristics of the present invention and advantage are:

1, adopt RSSI and two parameters that can from hardware register, obtain easily of LQI to position, be easy to realize, required hardware resource seldom, computation complexity is also very low;

2, be different from the past model and adopt RSSI and LQI empirical model, the present invention has obtained new range finding model based on RSSI and LQI by a large amount of experiments and data fitting, and checking has adaptability and generality preferably by experiment;

3, the data that obtain are averaged value filtering, the situation that the parameter that the filtering uncertain factor causes is excessive or too small;

4, aspect anchor node chooses, unite and consider RSSI value and LQI value, and make full use of beacon frame and carry to control and divide into groups the minimizing communication overhead;

5, be different from traditional centroid algorithm, introduce weighted factor, consider RSSI value and LQI value simultaneously, improved the reliability and the correctness of algorithm.

Description of drawings:

Fig. 1: wireless sensor network node structural representation in the embodiment of the invention;

Fig. 2: the flow chart of wireless sensor network node locating method in the example of the present invention;

Explanation of nouns:

Coordinator: coordinator node;

RSSI: received signal intensity indication;

LQI: link-quality indication;

LOC_Req: the positioning request information that unknown node is sent;

LOC_Reply: the location return information of anchor node;

Anchor_Threshold: satisfactory anchor node number threshold value;

RSSI_Threshold: unknown node is demarcated anchor node RSSI threshold value for the first time.

LQI_Threshold: unknown node is demarcated anchor node LQI threshold value for the first time.

R_Threshold: the RSSI threshold value when finally demarcating anchor node.

L_Threshold: the LQI threshold value when finally demarcating anchor node.

Embodiment:

Embodiment describes in further detail the present invention below in conjunction with accompanying drawing.

One. system configuration

Wireless sensor network is by the sensor node set U to be measured of many unknown positions and random distribution, known anchor node set A, coordinator node set C and aggregation node S set are formed, wherein aggregation node can be connected with Internet by wired or wireless mode, and Fig. 1 is an exemplary plot of the present invention.

Two. the selection of anchor node

According to shown in Figure 2, select the step of anchor node as follows:

1) for any unknown node u _i∈ U is with its power

Adjust to minimum P _Min, broadcast transmission Location Request LOC_Req.For anchor node a _j∈ A if it receives Location Request LOC_Req, then sends a reply LOC_Reply and gives unknown node.Unknown node u _iFrom LOC_Reply, obtain sending anchor node a _jRSSI and LQI, if RSSI＞RSSI_Threshold and LQI＞LQI_Threshold, then demarcate a _j, anchor node counter Anchor_Count adds 1.If Anchor_Count equals Anchor_Threshold, then stop this step, continue the 2nd) step.Otherwise improve Continue said process.

2) unknown node is with m the anchor node a that determines _j, j=1,2 ... the address information of m exists in the buffer memory of oneself as ID, and this information sent out broadcasts to local coordinator node c _p∈ C.

3) coordinator node c _pReceive u _iInformation after, send beacon frame and communicate by letter with the anchor node in the information.After anchor node was received beacon frame, the periodic broadcast beacon frame was given c _p

4) c _pTo the same anchor node a that receives _jRSSI and LQI get statistical average, subsequently to a _j, j=1,2 ... m sorts, and obtains

[I] anchor node set: Anchor_set={a ₁, a ₂..., a _m;

The RSSI value set of [II] anchor node correspondence: RSSI_set={r ₁, r ₂... r _m; r ₁＞r ₂＞...＞r _m

The LQI value set of [III] anchor node correspondence: LQI_set={l ₁, l ₂..., l _m; l ₁＞l ₂＞...＞l _m

5) the LQI fitting formula that obtains according to experimental data is determined L_Threshold, in RSSI_set and LQI_set, looks for l _qThe anchor node of＞L_Threshold, q=1,2 ... m obtains gathering LQI_Larger, for any l _tIf ∈ LQI_Larger is its RSSI value r _t＞R_Threshold, then it is the final anchor node of choosing, wherein the RSSI threshold value of R_Threshold for obtaining by classical RSSI range finding model.At last, obtaining the anchor node coordinate set is

Position_set＝{(x ₁，y ₁)，(x ₁，y ₂)，…，(x _n，y _n)}

Three. the weighting location algorithm

Anchor node coordinate for obtaining carries it into the weighted mass center formula

In can obtain the coordinate of unknown node, (x _Est, y _Est) be the coordinate of unknown node; (x _i, y _i) be the coordinate of anchor node i, retrain the influence of anchor node according to the energy difference of unknown node and anchor node to the unknown node position, introduced a weighted factor

In the formula E wherein _iBe anchor node u _iWith the energy difference of unknown node, rssi_val _iBe anchor node u _iThe RSSI value, rssi is the RSSI value of unknown node, LQI_val _iBe anchor node u _iThe LQI value, LQI is the LQI value of unknown node.Weighted factor w _iThe expression anchor node is near more apart from unknown node, and is big more to the position coordinates influence of unknown node.This restriction relation has improved the precision and the stability of location algorithm.Because RSSI and the LQI value collected are affected by the external environment, the situation that the anchor node that receives and the RSSI of unknown node, LQI value can occur equating is being calculated e _iIn time, introduces a δ and overcomes this problem.According to experimental results demonstrate, δ is taken as between the uniform (0.1,0.2) comparatively suitable, and wherein uniform represents even distribution.

By above process, realized wireless sensor network node locating method based on RSSI and LQI weighting.

Four. emulation experiment

In experiment, selected a square place of 10mx10m, disposed 12 anchor nodes and a telegon Coordinator node in the fixed position, placed 16 unknown node to be measured then at random.When initial, the transmitting power of unknown node is adjusted to minimum-20dBm, and the anchor node counter is initialized as zero, and satisfactory anchor node number threshold value A nchor Threshold is made as 6, RSSI_Threshold is set at-88dBm, and LQI_Threshold is set at 60dBm.Unknown node begins to send Location Request LOC_Req then, after anchor node receives request, replys LOC_Reply on every side.Finally obtain 6 anchor nodes that meet the location.Unknown node broadcasts to coordinator node Coordinator with 6 anchor node address informations.Coordinator and 6 anchor nodes communicate by beacon frame subsequently.Coordinator carries out the data acquisition of 100 times RSSI and LQI to each anchor node, according to experimental data, determines that the L_Threshold value is 70dBm, and the R_Threshold value is-85dBm.Obtain the anchor node coordinate set at last, anchor node coordinate number n is 4 in the set, locatees the coordinate of unknown node with these 4 anchor nodes.8 such experiments have been repeated altogether.

In order to weigh the accuracy of location, adopt following position error formula to estimate the performance of location algorithm

$\mathrm{location}\_\mathrm{error}=\sqrt{\frac{\underset{i=1}{\overset{N}{\mathrm{\Σ}}}[{(x_{\mathrm{esti}}-x_{\mathrm{real}})}^2+{(y_{\mathrm{esti}}-y_{\mathrm{real}})}^2]}{N}}$

(x wherein _Est, y _Est) the unknown node coordinate that draws of expression weighted mass center algorithm, (x _Real, y _Real) the real coordinate of expression unknown node, N is the number of times of experiment.

The weighted mass center location algorithm that adopts RSSI and LQI to combine, each unknown node coordinate that calculates, position error all remains in the 0.3m.This algorithm table reveals good accuracy and stability.

Claims (4)

1. based on the wireless sensor network node locating method of RSSI and LQI weighting, it is characterized in that: adopt RSSI range finding model to combine with LQI range finding model and carry out choosing and locating of anchor node, this method comprises the steps:

1.1) after unknown node enters network, seek anchor node by adjusting power, when the beacon frame that receives anchor node when unknown node outnumbers a certain threshold value, determine that anchor node number around it meets the demands and identifies, and sends to telegon Coordinator node with the anchor node information of establishing;

1.2) after telegon Coordinator node receives the information of unknown node, send beacon frame and communicate by letter with the anchor node in the information, after anchor node was received beacon frame, periodically broadcast beacon frame was to telegon Coordinator node;

1.3) after telegon Coordinator node receives beacon frame, anchor node is sorted and obtain its coordinate set according to the RSSI of anchor node and LQI value;

1.4) telegon Coordinator node is according to improved weighted mass center algorithm computation unknown node coordinate, and, be uploaded to Surveillance center through cable network by aggregation node to the aggregation node broadcast data.

2. the wireless sensor network node locating method based on RSSI and LQI weighting according to claim 1, it is characterized in that: described step 1) determines that the method for anchor node set is: after unknown node enters network, transmitting power is transferred to minimum value and is sent Location Request LOC_REQ, after receiving the answer LOC_Reply of anchor node, if meeting the requirements, the RSSI value of anchor node and LQI value then this anchor node is added to anchor node in this position fixing process, otherwise strengthen the unknown node transmitting power and send Location Request LOC_REQ once more, meet the required anchor node number in location up to finding.

3. the wireless sensor network node locating method based on RSSI and LQI weighting according to claim 1 is characterized in that: by the following method anchor node is sorted in the described step 3):

3.1) after telegon Coordinator node receives beacon frame, the RSSI and the LQI of same anchor node being got system mean value, telegon Coordinator is big or small according to the RSSI value of receiving anchor node and LQI value, and anchor node is sorted, and sets up three set:

[I] anchor node set: Anchor_set={a ₁, a ₂..., a _m;

The RSSI value set of [II] anchor node correspondence: RSSI_set={r ₁, r ₂... r _m; r ₁＞r ₂＞...＞r _m

The LQI value set of [III] anchor node correspondence: LQI_set={l ₁, l ₂..., l _m; l ₁＞l ₂＞...＞l _m

3.2) LQI fitting formula L (d)=L (d of obtaining according to experimental data ₀)-10nlg (d/d ₀)+X _δWith RSSI range finding model anchor node is carried out preferably, in the formula, d is the distance between the transmitter and receiver, d ₀Be reference distance, X _δBe that average is zero, variance is the random noise variable of δ, in RSSI_set and LQI_set set, select the higher anchor node of LQI value earlier, under this constraints, it is individual to select the higher anchor node n of RSSI value from the higher anchor node of LQI value again, draws the anchor node coordinate set and is:

Position_set＝{(x ₁，y ₁)，(x ₂，y ₂)，…，(x _n，y _n)}。

4. according to claim 1 or 3 described wireless sensor network node locating methods, it is characterized in that: obtain the unknown node coordinate in the described step 4) by the following method based on RSSI and LQI weighting:

4.1) with step 3.2) the improved weighted mass center algorithm of the anchor node coordinate set substitution formula that obtains:

$(x_{\mathrm{est}},y_{\mathrm{est}})=\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{w}_i(x_i,y_i)$

(x in the formula _Est, y _Est) be the coordinate of unknown node; (x _i, y _i) be the coordinate of anchor node i, retrain the influence of anchor node according to the energy difference of unknown node and anchor node to the unknown node position, introduced a weighted factor

$w_i=\frac{1/e_i^2}{\underset{i=1}{\overset{n}{\mathrm{\Σ}}}1/e_i^2}$

In the formula $e_i=\sqrt{{(\mathrm{rssi}\_{\mathrm{val}}_i+\mathrm{\δ}-\mathrm{rssi})}^2+{(\mathrm{LQI}\_{\mathrm{val}}_i+\mathrm{\δ}-\mathrm{LQI})}^2}$

e _iBe anchor node u _iWith the energy difference of node to be measured, rssi_val _iBe anchor node u _iThe RSSI value, rssi is the RSSI value of node to be measured, LQI_val _iBe anchor node u _iThe LQI value, LQI is the LQI value of node to be measured, weighted factor w _iExpression anchor node distance node to be measured is near more, and big more to the position coordinates influence of node to be measured, this restriction relation has improved the precision and the stability of location algorithm;

4.2) because RSSI and the LQI value collected are affected by the external environment, the situation that the anchor node that receives and the RSSI of unknown node, LQI value can occur equating is being calculated e _iIn time, introduces a δ and overcomes this problem, and according to experimental results demonstrate, δ is taken as between the uniform (0.1,0.2) comparatively suitable, and wherein uniform represents even distribution.

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